Both Patients and Plastic Surgeons Prefer Artificial Intelligence-Generated Microsurgical Information
Thieme. All rights reserved..
BACKGROUND: With the growing relevance of artificial intelligence (AI)-based patient-facing information, microsurgical-specific online information provided by professional organizations was compared with that of ChatGPT (Chat Generative Pre-Trained Transformer) and assessed for accuracy, comprehensiveness, clarity, and readability.
METHODS: Six plastic and reconstructive surgeons blindly assessed responses to 10 microsurgery-related medical questions written either by the American Society of Reconstructive Microsurgery (ASRM) or ChatGPT based on accuracy, comprehensiveness, and clarity. Surgeons were asked to choose which source provided the overall highest-quality microsurgical patient-facing information. Additionally, 30 individuals with no medical background (ages: 18-81, μ = 49.8) were asked to determine a preference when blindly comparing materials. Readability scores were calculated, and all numerical scores were analyzed using the following six reliability formulas: Flesch-Kincaid Grade Level, Flesch-Kincaid Readability Ease, Gunning Fog Index, Simple Measure of Gobbledygook Index, Coleman-Liau Index, Linsear Write Formula, and Automated Readability Index. Statistical analysis of microsurgical-specific online sources was conducted utilizing paired t-tests.
RESULTS: Statistically significant differences in comprehensiveness and clarity were seen in favor of ChatGPT. Surgeons, 70.7% of the time, blindly choose ChatGPT as the source that overall provided the highest-quality microsurgical patient-facing information. Nonmedical individuals 55.9% of the time selected AI-generated microsurgical materials as well. Neither ChatGPT nor ASRM-generated materials were found to contain inaccuracies. Readability scores for both ChatGPT and ASRM materials were found to exceed recommended levels for patient proficiency across six readability formulas, with AI-based material scored as more complex.
CONCLUSION: AI-generated patient-facing materials were preferred by surgeons in terms of comprehensiveness and clarity when blindly compared with online material provided by ASRM. Studied AI-generated material was not found to contain inaccuracies. Additionally, surgeons and nonmedical individuals consistently indicated an overall preference for AI-generated material. A readability analysis suggested that both materials sourced from ChatGPT and ASRM surpassed recommended reading levels across six readability scores.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2024 |
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| Enthalten in: |
Journal of reconstructive microsurgery - (2024) vom: 26. März |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Berry, Charlotte E [VerfasserIn] |
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| Links: |
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Date Revised 26.03.2024 published: Print-Electronic Citation Status Publisher |
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| doi: |
10.1055/a-2273-4163 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM368726495 |
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| 520 | |a Thieme. All rights reserved. | ||
| 520 | |a BACKGROUND: With the growing relevance of artificial intelligence (AI)-based patient-facing information, microsurgical-specific online information provided by professional organizations was compared with that of ChatGPT (Chat Generative Pre-Trained Transformer) and assessed for accuracy, comprehensiveness, clarity, and readability | ||
| 520 | |a METHODS: Six plastic and reconstructive surgeons blindly assessed responses to 10 microsurgery-related medical questions written either by the American Society of Reconstructive Microsurgery (ASRM) or ChatGPT based on accuracy, comprehensiveness, and clarity. Surgeons were asked to choose which source provided the overall highest-quality microsurgical patient-facing information. Additionally, 30 individuals with no medical background (ages: 18-81, μ = 49.8) were asked to determine a preference when blindly comparing materials. Readability scores were calculated, and all numerical scores were analyzed using the following six reliability formulas: Flesch-Kincaid Grade Level, Flesch-Kincaid Readability Ease, Gunning Fog Index, Simple Measure of Gobbledygook Index, Coleman-Liau Index, Linsear Write Formula, and Automated Readability Index. Statistical analysis of microsurgical-specific online sources was conducted utilizing paired t-tests | ||
| 520 | |a RESULTS: Statistically significant differences in comprehensiveness and clarity were seen in favor of ChatGPT. Surgeons, 70.7% of the time, blindly choose ChatGPT as the source that overall provided the highest-quality microsurgical patient-facing information. Nonmedical individuals 55.9% of the time selected AI-generated microsurgical materials as well. Neither ChatGPT nor ASRM-generated materials were found to contain inaccuracies. Readability scores for both ChatGPT and ASRM materials were found to exceed recommended levels for patient proficiency across six readability formulas, with AI-based material scored as more complex | ||
| 520 | |a CONCLUSION: AI-generated patient-facing materials were preferred by surgeons in terms of comprehensiveness and clarity when blindly compared with online material provided by ASRM. Studied AI-generated material was not found to contain inaccuracies. Additionally, surgeons and nonmedical individuals consistently indicated an overall preference for AI-generated material. A readability analysis suggested that both materials sourced from ChatGPT and ASRM surpassed recommended reading levels across six readability scores | ||
| 650 | 4 | |a Journal Article | |
| 700 | 1 | |a Fazilat, Alexander Z |e verfasserin |4 aut | |
| 700 | 1 | |a Lavin, Christopher |e verfasserin |4 aut | |
| 700 | 1 | |a Lintel, Hendrik |e verfasserin |4 aut | |
| 700 | 1 | |a Cole, Naomi |e verfasserin |4 aut | |
| 700 | 1 | |a Stingl, Cybil S |e verfasserin |4 aut | |
| 700 | 1 | |a Valencia, Caleb |e verfasserin |4 aut | |
| 700 | 1 | |a Morgan, Annah G |e verfasserin |4 aut | |
| 700 | 1 | |a Momeni, Arash |e verfasserin |4 aut | |
| 700 | 1 | |a Wan, Derrick C |e verfasserin |4 aut | |
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